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This chapter focuses on the need for fine-grained social mixingSocial mixing and mobilityMobility data to devise mitigation strategies and more accurately predict pathogenic spread before and during pandemics. We explore the availability of different data types and discuss our efforts to collect individual-level indoor movement data to measure patterns of social interaction in a congregate setting. To do so, we deployed a dense BluetoothBluetooth network and developed aSmartphone smartphone-based app to record the signal strength and connection duration of BluetoothBluetooth beacons and Wi-FiWi-Fi routers. Over a two-week study period in November 2023, we recorded 135 million data points from 122 unique participant devices. We outline ways signal strength data can be used to calculate a participant's place in space and time, allowing us to map the social interactions of study participants. We argue that these types of data are necessary to make informed decisions when planning targeted interventions in congregate settingsCongregate settings, which can aid in our ability to predict and prevent future pandemics.

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Measuring Mobility and Social Mixing to Inform Pandemic Prediction and Response

  • 章节

  • 发表日期：

    2026年

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  • Peyton Luiz,
  • Jason R. Gantenberg,
  • Samuel F. Rosenblatt,
  • Guixing Wei,
  • Aditya Khanna,
  • Bryn C. Loftness,
  • Mark N. Lurie

摘要

This chapter focuses on the need for fine-grained social mixingSocial mixing and mobilityMobility data to devise mitigation strategies and more accurately predict pathogenic spread before and during pandemics. We explore the availability of different data types and discuss our efforts to collect individual-level indoor movement data to measure patterns of social interaction in a congregate setting. To do so, we deployed a dense BluetoothBluetooth network and developed aSmartphone smartphone-based app to record the signal strength and connection duration of BluetoothBluetooth beacons and Wi-FiWi-Fi routers. Over a two-week study period in November 2023, we recorded 135 million data points from 122 unique participant devices. We outline ways signal strength data can be used to calculate a participant's place in space and time, allowing us to map the social interactions of study participants. We argue that these types of data are necessary to make informed decisions when planning targeted interventions in congregate settingsCongregate settings, which can aid in our ability to predict and prevent future pandemics.